Start calling this model with endpoint-specific examples.
Headline benchmark standings and comparison context.
Key dates, capabilities, and model metadata.
Start calling this model with endpoint-specific examples.
Headline benchmark standings and comparison context.
Key dates, capabilities, and model metadata.
Start calling this model with endpoint-specific examples.
Headline benchmark standings and comparison context.
Key dates, capabilities, and model metadata.
19 Jan 2026
19 Jan 2026
License
MIT
Input
Output
Headline benchmark standings and comparison context.
Top benchmark results for z-ai/glm-4.7-flash.
Detailed benchmark comparisons now live in the Compare tool.
Core latency and throughput trends from recent traffic.
Latency
Throughput
Uptime
Latency
Throughput
Uptime
Latency
Throughput
Uptime
Latency
Throughput
Uptime
Latency
Throughput
Uptime
Latency
Throughput
Uptime
Latency
Throughput
Uptime
Latency
Throughput
Uptime
Start calling this model with endpoint-specific examples.
Choose a supported endpoint, pick a main language, then select the example style you want to copy.
import AIStats from '@ai-stats/sdk';
const client = new AIStats({
apiKey: process.env.AI_STATS_API_KEY,
});
const response = await client.generateResponse({
"model": "z-ai/glm-4.7-flash",
"input": "Give me one fun fact about cURL.",
"service_tier": "standard"
});
const outputText = response.output
?.flatMap((item) => item.content ?? [])
.find((item) => item.type === "output_text")
?.text;
console.log(outputText ?? response);Parameters
Aggregated across active providers for the responses route.
Routing will select a compatible provider when a parameter narrows availability, so this list stays model-facing instead of provider-facing.
| Parameter | Description |
|---|---|
temperature | Controls how random token selection can be. |
top_p | Applies nucleus sampling by limiting candidates to a probability mass threshold. |
max_tokens | Caps output length on endpoints and providers that use the max_tokens field name. |
tools | Defines callable tools or functions the model can invoke. |
top_k | Restricts sampling to the top-k candidate tokens on providers that expose it. |
frequency_penalty | Discourages repeated tokens in proportion to how often they already appeared. |
presence_penalty | Encourages the model to explore new wording or topics after they first appear. |
repetition_penalty | Applies provider-specific anti-repetition behavior outside the classic penalty fields. |
seed | Requests deterministic sampling when the upstream provider supports seeded generation. |
stop | Defines one or more sequences that terminate generation early. |
logprobs | Requests token-level probability data in the response. |
tool_choice | Controls which tool, if any, the model should call. |
response_format | Requests plain text, JSON, or schema-constrained output formats. |
structured_outputs | Capability signal for reliable schema-constrained output workflows. |
include_reasoning | Requests reasoning content or reasoning summaries in responses where supported. |
logit_bias | Adjusts token selection bias directly when a provider exposes logit control. |
min_p | Narrows sampling by discarding tokens below a minimum probability threshold. |
reasoning_enabled | See the full parameter reference for endpoint-specific semantics and provider caveats. |
top_logprobs | Limits how many alternative token probabilities are returned per position. |
Select a route to update the request snippet and compatibility details.
/v1/responses/v1/chat/completions/v1/messages